Learning Statistics with Python
Correlation describes the degree to which two variables move in coordination with one another.
With the correlation, we can easily examine the result. The correlation can be the number in the interval
[-1; 1]. Look at the table:
|The value of correlation||Meaning|
|1||The perfect positive correlation; if the one value increase, the other increases too, and vice versa|
|0||There is no correlation|
|-1||The perfect negative correlation; if the one value increase, the other decreases, and vice versa|
Correlation with Python:
To calculate correlation, we will use the function from NumPy
np.corrcoef() with two parameters: the sequences of data between which we want to find correlation. Look at the example:
Here, we will extract the number with the index [0, 1] — the same as in the case with covariance.
In the previous chapter, we received the number
74955.85, analyzing the result of the applying correlation function is hard. But, here, we can conclude that the values are related almost perfectly.